df=pd.read_csv(os.path.join(directory,'1.csv'))



cols =['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',

    'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
    'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']

df.iloc[:-1, [df.columns.get_loc(c) for c in cols]].replace(',', '', regex=True).apply(pd.to_numeric)


df[['Order Qty (SL)','Confirmed Qty (SL)','Unconfirmed Qty (SL)','Cancelled Qty (SL)','Open Qty (SL)','Reserved Qty (SL)',

    'Fixed Qty (SL)','% Allocation (SL)','Delivered Qty (SL)','PGI Qty (SL)','Invoiced Qty (SL)',
    'Net Unit Price','Confirmed Net Value (SL)','Dollars Shipped (SL)','% Shipped/Allocated (SL)']] /= 1000